Multi-layer protection system construction
The TPO framework has a triple security mechanism built in:
technical realization
- Reward Model Screening::
- Mandatory loading of safety assessment models (e.g. Safety-RM)
- Setting in config.yaml
safety_threshold: 0.7
- Iterative process control::
- Execute after each round of generation
check_safety()function (math.) - Hazardous content automatically triggers the regeneration process
- Execute after each round of generation
- Output Post-Processing::
- Integration of HuggingFace
text-filterassemblies - Fuzzification of sensitive information (regular expression matching)
- Integration of HuggingFace
operational strategy
- Establishment of a dynamic list of sensitive terms (hourly synchronized updates)
- Setting up an audit workflow: high-risk outputs need to be reviewed manually
- Full logging: all iterations are archived for review
Test data show that the program can control the harmful content generation rate below 0.3%.
This answer comes from the articleTPO-LLM-WebUI: An AI framework where you can input questions to train a model to output results in real timeThe
May not be reproduced without permission:AI productivity tools " How to avoid security risk outputs during large model optimization?
